Deep Sea Research Part II: Topical Studies in Oceanography
The threshold feeding response of microzooplankton within Pacific high-nitrate low-chlorophyll ecosystem models under steady and variable iron input
Introduction
Large portions of the equatorial and oceanic pacific have been classified as being high-nitrate low-chlorophyll (HNLC) regimes (Martin et al., 1991; Chisholm and Morel, 1991; Frost and Kishi, 1999). Both field process studies, such as EqPac (Murray et al., 1994; Landry et al., 1995a; Landry et al., 1995b; Verity et al., 1996), and modeling studies (Frost and Franzen, 1992; Loukos et al., 1997; Pitchford and Brindley, 1999) have confirmed the importance of the microbial loop in the structure and maintenance of the HNLC condition. The current paradigm is that the growth rates of large phytoplankton are limited by the rate of nutrient input (iron), whereas growth and standing stock of small phytoplankton biomass, which constitutes the majority of total phytoplankton, is limited through tight grazing control by the microzooplankton and recycling efficiency (Banse, 1992; Frost and Franzen, 1992; Landry et al., 1997). Because of this tight coupling between the microzooplankton and phytoplankton, a critical component of any ecosystem model describing an HNLC system is the form of the functional response used to represent the grazing of the microzooplankton community on the phytoplankton community.
Many ecosystem models typically use a Michaelis-Menten or similar Type II (Holling, 1959) function with some kind of grazing threshold (Fig. 1) to describe the functional response of zooplankton grazing. The grazing threshold, or “lower feeding threshold,” is defined as the concentration of prey, below which, the predator stops feeding. An alternative is to use a Type III (sigmoidal, Holling, 1959) functional response, which, due to the inflection in ingestion rate as the prey concentration decreases, acts the same as a threshold model (Steele, 1974a; Steele and Mullin, 1977). Steele 1974a, Steele 1974b first pointed out the importance of the grazing function in controlling the dynamics of a planktonic food web, and suggested that a lower feeding threshold is actually critical to stabilize these models. Essentially, without the lower threshold it is assumed that predators can completely eliminate their prey, which is not likely in nature. The other possibilities that result when a threshold is not included are chaotic fluctuations or stable limit cycles (Steele and Henderson, 1992). The existence of a lower grazing threshold for individual zooplankton predators feeding on a single prey type has both theoretical (Steele, 1974b; Strom et al., 2000) and experimental (some of which is equivocal) support (Frost, 1974; Rivier et al., 1985; Verity, 1991; Choi, 1994; Lessard and Murrell, 1998). However, the existence of this threshold has never been confirmed for the specific microzooplankton assemblage of the equatorial Pacific HNLC.
An “apparent” threshold also can be observed, even if an individual zooplankton species does not have a grazing threshold, if multiple prey types are present (Fasham et al., 1990). This is because when two (or more) acceptable prey types are present, a predator should eat proportionally more of the more abundant prey type, or the predator may switch between prey items. Thus, the shape of the functional response of a predator on one individual prey item could show either a threshold or sigmoidal shape at low prey concentrations (Fig. 1). Franks et al. (1986) showed that inclusion of a sigmoidal Type III-like function (the function was Type III only at lower concentrations of prey) provided model stability in a simple nitrogen–phytoplankton–zooplankton (NPZ) model. Fasham (1995) also found that a Type III model resulted in greater model stability in a somewhat more complicated ecosystem model. Several ecosystem models have taken this approach to modeling an HNLC food web; i.e. they include no lower feeding threshold, but rather a “perceived” threshold on a single prey item due to the availability of multiple prey (Fasham et al., 1990; Loukos et al., 1997; Pitchford and Brindley, 1999). Thus, ecosystem models of HNLC regimes so far have always included either a threshold (or Type III response) or prey-switching ability of the microzooplankton in order to achieve the HNLC condition; without these assumptions in the model structure, models may not produce an HNLC regime (Strom et al., 2000). However, the particular formulation used to model prey switching is very critical, as most commonly used formulations contain both mathematical and conceptual inconsistencies (Gentleman et al., 2003).
One of the stated goals of the Joint Global Ocean Flux Study (JGOFS) is to develop a simple useful model that matches local data well, and can eventually be extrapolated to other areas (Evans, 1999). Before models that are fit to local data can do this, the potential impacts of the assumptions described above must be more thoroughly addressed for the microzooplankton inhabiting the HNLC equatorial Pacific. Addressing these assumptions concerning the grazing function is doubly important for both increasing the predictive ability of such models when coupled to larger-scale physical models, and to increase our basic mechanistic understanding of how the food web functions. Here, we tested the hypothesis that inclusion of a lower feeding threshold is necessary to achieve an HNLC system. We also compared the sensitivity of daily primary production and phytoplankton standing stock within different forms of a microzooplankton grazing response (threshold versus no threshold versus Type III). The overall goal of this work was to analyze the appropriateness of the microzooplankton grazing functions currently used in most ecosystem models, and address their impact (faulty or otherwise) on predictions of primary production and carbon export made from such models. In a later contribution, we shall address the second assumption implicit in many ecosystem models; the formulation used for feeding on multiple prey types (Gentleman et al., 2003).
Section snippets
Methods
The starting point for our analysis of the inclusion of a feeding threshold is the model of Frost and Franzen (1992; referred to hereafter as the FF model). This model simulates the HNLC region by analogy to a chemostat. The basic principle of a chemostat is that nutrients are added to a system containing some assemblage of phytoplankton and grazers, the contents are mixed, the phytoplankton and zooplankton grow, and then the contents are diluted out of the system at the same flow rate as that
Sensitivity analysis
Results of the sensitivity analyses for the three versions of the model for both the constant forcing runs and the seasonally variable runs are summarized in Appendix Table 4, Table 5, respectively. The relative trends in sensitivity were nearly identical within each model type between the constant and seasonally variable runs. For all runs, all three models showed zero sensitivity to the initial concentration of nitrogen, phytoplankton, or zooplankton. For average daily primary productivity,
Discussion
The modeling exercise conducted here is a good example of the sensitivity of simplified food web models to the formulations used to control the flux of material between trophic levels—primarily the grazing function. The choice of a grazing function is particularly critical in HNLC systems in which there is a very tight coupling between the microzooplankton and their small phytoplankton prey. We found that without the inclusion of a feeding threshold, our traditionally parameterized Type II
Acknowledgements
This work was supported by a Postdoctoral fellowship from the University of Washington, College of Ocean and Fisheries Sciences to A. Leising, and NSF grant OCE 9504202 to J.W. Murray, B.W. Frost, and S.L. Strom. AWL would like to thank the SMP at UW modeling group: Jim, Bruce, Wendy, and Susanne for many stimulating conversations concerning this work, along with the comments and helpful feedback from the attendees at the SMP JGOFS workshops, held at Woods Hole. Finally, we would like to thank
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Current address: Pacific Fisheries Environmental Laboratory, 1352 Lighthouse Ave., Pacific Grove, CA 93950, USA.